Missouri tax and benefit system#
This notebook shows how the state and federal tax and benefit system affects Missouri residents holistically.
Examples#
Consider a set of Missouri family types, each with $1,000 monthly rent and $50 monthly broadband costs, and varying in terms of marital status and number of children. Their net income—after state and federal taxes and benefits modeled by PolicyEngine US—is shown in the graph below.
from policyengine_us import IndividualSim
import pandas as pd
import plotly.express as px
LIGHT_GRAY = "#F5F5F5"
GRAY = "#BDBDBD"
BLUE = "#5091cc"
LIGHT_BLUE = "lightblue"
DARK_BLUE = "darkblue"
def make_tax(adults, children):
sim = IndividualSim(year=2022)
sim.add_person(name="head", age=70, rent=12_000)
members = ["head"]
if adults == 2:
sim.add_person(name="spouse", age=25)
members += ["spouse"]
for i in range(children):
child = "child{}".format(i)
sim.add_person(name=child, age=6)
members += [child]
sim.add_tax_unit(name="tax_unit", members=members, premium_tax_credit=0)
# $1,000 monthly rent, $50 monthly broadband.
sim.add_spm_unit(name="spm_unit", members=members, broadband_cost=600)
sim.add_household(name="household", members=members, state_code="MO")
sim.vary("employment_income", max=100_000, step=100)
employment_income = sim.calc("employment_income")[0]
spm_unit_net_income = sim.calc("spm_unit_net_income")[0].round()
mtr = 1 - sim.deriv(
"spm_unit_net_income", "employment_income", wrt_target="head"
)
return pd.DataFrame(
dict(
employment_income=employment_income,
spm_unit_net_income=spm_unit_net_income,
mtr=mtr,
adults=adults,
children=str(children),
)
)
# Make a table of state taxes for different numbers of adults and children.
l = []
for adults in range(1, 3):
for children in range(0, 4):
l.append(make_tax(adults, children))
df = pd.concat(l)
LABELS = dict(
employment_income="Employment income",
spm_unit_net_income="Net income",
mtr="Marginal tax rate",
adults="Adults",
children="Children",
)
COLOR_MAP = {"0": GRAY, "1": LIGHT_BLUE, "2": BLUE, "3": DARK_BLUE}
fig = px.line(
df,
"employment_income",
"spm_unit_net_income",
color="children",
animation_frame="adults",
labels=LABELS,
title="Net income for a Missouri household",
color_discrete_map=COLOR_MAP,
)
fig.update_layout(
xaxis_tickformat="$,",
yaxis_tickformat="$,",
plot_bgcolor="white",
xaxis_gridcolor=LIGHT_GRAY,
yaxis_gridcolor=LIGHT_GRAY,
)
fig.show()
WARNING:root:Parameter gov.states.ct.tax.income.rebate.reduction.start has a child WIDOW that is not in the possible values of filing_status, ignoring.
WARNING:root:Parameter gov.states.ct.tax.income.rebate.reduction.start has a child WIDOW that is not in the possible values of filing_status, ignoring.
WARNING:root:Parameter gov.states.ct.tax.income.rebate.reduction.start has a child WIDOW that is not in the possible values of filing_status, ignoring.
WARNING:root:Parameter gov.states.ct.tax.income.rebate.reduction.start has a child WIDOW that is not in the possible values of filing_status, ignoring.
WARNING:root:Parameter gov.states.ct.tax.income.rebate.reduction.start has a child WIDOW that is not in the possible values of filing_status, ignoring.
WARNING:root:Parameter gov.states.ct.tax.income.rebate.reduction.start has a child WIDOW that is not in the possible values of filing_status, ignoring.
WARNING:root:Parameter gov.states.ct.tax.income.rebate.reduction.start has a child WIDOW that is not in the possible values of filing_status, ignoring.
WARNING:root:Parameter gov.states.ct.tax.income.rebate.reduction.start has a child WIDOW that is not in the possible values of filing_status, ignoring.
WARNING:root:Parameter gov.states.ct.tax.income.rebate.reduction.start has a child WIDOW that is not in the possible values of filing_status, ignoring.
Total marginal tax rates range from below -50% to above 50%.
fig = px.line(
df,
"employment_income",
"mtr",
color="children",
animation_frame="adults",
labels=LABELS,
title="Marginal tax rate for a Missouri household",
color_discrete_map=COLOR_MAP,
)
fig.update_layout(
xaxis_tickformat="$,",
yaxis_tickformat=".1%",
yaxis_range=[-1, 5],
plot_bgcolor="white",
xaxis_gridcolor=LIGHT_GRAY,
yaxis_gridcolor=LIGHT_GRAY,
)
fig.show()
Other situations#
A single person who is age 65 and holds less than $2,000 in assets will be eligible for additional tax exemptions and federal Supplemental Security Income (SSI).
sim = IndividualSim(year=2022)
sim.add_person(
name="head",
age=65,
rent=1_000,
)
sim.add_tax_unit(name="tax_unit", members=["head"], premium_tax_credit=0)
sim.add_spm_unit(name="spmu", members=["head"])
sim.add_household(name="h", members=["head"], state_code="MO")
sim.vary("employment_income", max=100_000, step=100)
employment_income = sim.calc("employment_income")[0]
spm_unit_net_income = sim.calc("spm_unit_net_income")[0].round()
mtr = 1 - sim.deriv(
"spm_unit_net_income", "employment_income", wrt_target="head"
)
df = pd.DataFrame(
dict(
employment_income=employment_income,
spm_unit_net_income=spm_unit_net_income,
mtr=mtr,
)
)
fig = px.line(
df,
"employment_income",
"spm_unit_net_income",
labels=LABELS,
title="Net income for a single person aged 65 in Missouri",
)
fig.update_layout(
xaxis_tickformat="$,",
yaxis_tickformat="$,",
plot_bgcolor="white",
xaxis_gridcolor=LIGHT_GRAY,
yaxis_gridcolor=LIGHT_GRAY,
)
fig.show()
WARNING:root:Parameter gov.states.ct.tax.income.rebate.reduction.start has a child WIDOW that is not in the possible values of filing_status, ignoring.
fig = px.line(
df,
"employment_income",
"mtr",
labels=LABELS,
title="Marginal tax rate for a single person aged 65 in Missouri",
)
fig.update_layout(
xaxis_tickformat="$,",
yaxis_tickformat=".1%",
yaxis_range=[0, 1],
plot_bgcolor="white",
xaxis_gridcolor=LIGHT_GRAY,
yaxis_gridcolor=LIGHT_GRAY,
)
fig.show()